Method and system for optimized monitoring and identification of advanced metering infrastructure device communication failures

1. A computer-implemented method for optimized monitoring and identification of Advanced Metering Infrastructure (AMI) device communication failures in an AMI network via a processor executing program instructions stored in a memory, the computer-implemented method comprising: generating, via the processor, a graphical representation of the AMI devices, the graphical representation comprising nodes corresponding to the AMI devices and links representing the connectivity between the AMI devices, wherein the graphical representation is generated based on data associated with the AMI devices retrieved via the AMI network in real-time; computing, via the processor, one or more properties of the AMI devices using the graphical representation, wherein the one or more properties are computed based on values associated with the nodes corresponding to the AMI devices in the graphical representation; modifying, via the processor, the graphical representation based on the computed one or more properties and one or more predefined rules, wherein the nodes corresponding to the AMI devices are updated based on the computed one or more properties and the one or more links are modified based on the one or more predefined rules; selecting, via the processor, one or more nodes in the modified graphical representation and processing the selected nodes in an order based on AMI device hierarchy, priority and criticality; modifying, via the processor, the graphical representation based on the processing of the selected nodes; and identifying AMI device with communication failures from at least one of the generated and modified graphical representation of the AMI devices.

2. The computer-implemented method of claim 1 , wherein generating a graphical representation of the AMI devices comprises: generating a directed graph including Bottleneck Network Element (BNE) nodes representing corresponding access points in the AMI network, Trailed Network Element (TNE) nodes representing smart meters and relays in the AMI network, and Virtual-Trailed Network Element nodes (V-TNE) representing the connection between smart meters and relays; categorizing the generated nodes into a plurality of regions, wherein the plurality of regions represent the geographical area comprising the AMI devices; and characterizing each generated node of the region based on one or more parameters, wherein the one or more parameters comprise region code, predefined R-factor associated with each node-relationship, Type-Factor (T-Factor) related to the type of the AMI devices, and TOD-weight related to the time of operation of the AMI devices, and provisioned Bellwether nodes.

3. The computer-implemented method of claim 2 , wherein computing one or more properties of the AMI devices using the graphical representation comprises: generating an order to select BNE nodes from any selected region of the plurality of regions based on the one or more parameters; obtaining latency values associated with the BNE nodes in the selected region, wherein the BNE nodes in the graphical representation are updated with latency values by analyzing pinging responses from the corresponding access points; and obtaining node-count values associated with the BNE nodes in the selected region, wherein the BNE nodes in the graphical representation are updated with node-count values which represent the number of TNE nodes that are attached to the BNE nodes.

4. The computer-implemented method of claim 3 , wherein modifying the graphical representation based on the computed one or more properties and one or more predefined rules comprises: updating the links of BNE nodes of the generated graph based on the obtained latency values associated with the BNE nodes and the obtained node-count values.

5. The computer-implemented method of claim 4 , wherein computing one or more properties of the AMI devices using the graphical representation comprises: computing priority values for each BNE node in the selected region based on at least the latency values and the node-count values.

7. The computer-implemented method of claim 6 , selecting one or more nodes in the modified graphical representation and processing the selected nodes in the order based on AMI device hierarchy, priority and criticality comprises: selecting the order of BNE nodes in the selected region based on the BNE node priority values from the highest to the lowest; and categorizing the communication failure at BNE level as hierarchical communication failure.

8. The computer-implemented method of claim 7 , wherein computing one or more properties of the AMI devices using the graphical representation further comprises: obtaining the nodes that are not identified with hierarchical communication failure and identifying debouncing nodes from the obtained nodes, wherein the debouncing nodes are nodes with least probability of communication failure; and calculating debouncing delay for the debouncing nodes, wherein debouncing delay is the time-duration after which the debouncing nodes are pinged to check for any communication failure.

9. The computer-implemented method of claim 8 , wherein the debouncing delay is calculated using the formula: Ddbn=[Thr(ToD(hcur))*60*60]/n(req).

10. The computer-implemented method of claim 9 , wherein modifying the graphical representation based on the computed one or more properties and one or more predefined rules comprises updating the BNE nodes in the graphical representation based on the obtained nodes that are not identified with hierarchical communication failure and separating the updated BNE nodes from the identified debouncing nodes.

11. The computer-implemented method of claim 10 , wherein computing one or more properties of the AMI devices using the graphical representation further comprises computing priority values for BNE nodes and TNE nodes not identified as debouncing nodes based on at least the latency values and the node-count values.

12. The computer-implemented method of claim 11 , wherein the priority of each BNE nodes and TNE nodes is calculated using the formula: P=L/A+((T*pCnt)+(pCnt*hConstant))+(T*lCnt)+B/W where, A is average latency of all responding nodes, L is Previous latency, T is T-Factor of the BNE, B is Bellwether flag, Total number of Bellwether nodes in given region (W) and Total number BNEs (pCnt) and TNEs (lCnt).

13. The computer-implemented method of claim 11 , wherein selecting nodes in the modified graphical representation and processing the selected nodes of the selected region for categorizing the nodes based on AMI device hierarchy, priority and criticality comprises: selecting the BNE nodes in order of their priority from highest priority to lowest priority; calculating criticality of the TNE nodes associated with the selected BNE nodes; and selecting the TNE nodes in order of their criticality from highest to lowest for identifying any AMI device communication failure.

14. The computer-implemented method of claim 13 , further comprising: calculating critical factor (cf) of each TNE node using priority and average latency of each TNE node for past known hours using the following formula cf=(priority average node latency).

15. The computer-implemented methods of claim 13 further comprising: ascertaining nested device communication failure if all the TNE nodes are identified with device communication failure; traversing the graphical representation to identify all V-TNE nodes if the all the TNE nodes are not identified for device communication failure; updating priority values and Bellwether nodes for each node of the V-TNE nodes; modifying the graphical representation of V-TNE node for each of its node; calculating criticality of each node of the V-TNE node; and selecting the TNE nodes of selected V-TNE node in order of their criticality from highest criticality to lowest criticality for identifying any device communication failure.

16. The computer-implemented method of claims 12 and 13 , wherein criticality of the TNE nodes of V-TNE nodes are calculated by obtaining network communication history of the TNE and V-TNE nodes for a predefined time period; computing latency based on pinging responses received from the TNE and V-TNE nodes; sorting the TNE and V-TNE nodes in an increasing order of computed latency, wherein the node with maximum average latency is identified as the node with highest criticality.

17. The computer-implemented method of claim 8 , wherein debouncing nodes are identified by: calculating past network performance of the BNE nodes and the TNE nodes for predefined hours; calculating failure probability of the BNE nodes and the TNE nodes based on at least one of past iterations, number of device ping requests and number of failed ping-requests; calculating device-ping-rate-per-hour for the BNE nodes and the TNE nodes; calculating multiple-ping-probability of the BNE nodes and the TNE nodes; and identifying DBN nodes based on the calculated values.

18. The computer-implemented method of claim 17 further comprising: updating the graphical representation with debouncing nodes in order to determine if node should be pinged or not for the duration equal to debouncing-delay; obtaining node-relationships for each debouncing-nodes; calculating weight of each relationships; selecting the node-relationships in order of their weight from highest to lowest; selecting and processing each node of the node-relationship in order to detect any hierarchical, nested or device communication failure based on one or more parameter of the node; and updating one or more properties of the nodes in the graphical representation and sending next device-ping request after the time equal to debouncing delay.

19. The computer-implemented method of claim 18 , wherein each of the node-relationship and corresponding weight is calculated by: obtaining regions codes of all debouncing nodes; generating sets of nodes sharing one or more common properties and one or more common parameters including region entity, region number, region name and node level; and calculating weight of each relationships as represented by regional, inter-regional and intra-regional relationship weight based on total number of debouncing nodes in a given node-relationships, priority of each debouncing node and R-factor of each relationship.

20. A system for optimized monitoring and identification of Advanced Metering Infrastructure (AMI) device communication failures in an AMI network for detecting communication failures, the system comprising: an AMI graph generating unit in communication with a processor and configured to generate a graphical representation of the AMI devices, the graphical representation comprising nodes corresponding to the AMI devices and links representing the connectivity between the AMI devices, wherein the graphical representation is generated based on data associated with the AMI devices retrieved via the AMI network in real-time; an AMI device monitoring unit in communication with the processor and configured to modify, via the AMI graph generating unit, the graphical representation based on computed one or more properties and one or more predefined rules associated with the nodes; and an AMI device communication failure identification unit in communication with the processor and configured to compute priority and criticality of the nodes using the modified graphical representation, wherein the nodes are categorized and processed based on AMI device hierarchy priority and criticality for detecting AMI device communication failures.

21. The system of claim 20 further comprising an AMI data repository in communication with the processor and configured to store data associated with the nodes that are computed using the graphical representation.

22. The system of claim 20 further comprising an AMI data retrieval unit in communication with the processor and configured to retrieve data associated with the AMI devices in the AMI network.

23. The system of claim 20 , wherein the predefined rules comprise rules for modifying the links in the graphical representation between the nodes based on the computed one or more properties.

24. A computer program product comprising: a non-transitory computer-readable medium having computer-readable program code stored thereon, the computer-readable program code having program instructions, when executed by a processor, cause the processor to: generate a graphical representation of the AMI devices, the graphical representation comprising nodes corresponding to the AMI devices and links representing the connectivity between the AMI devices, wherein the graphical representation is generated based on data associated with the AMI devices retrieved via the AMI network in real-time; compute one or more properties of the AMI devices using the graphical representation, wherein the one or more properties are computed based on values associated with the nodes corresponding to the AMI devices in the graphical representation; modify the graphical representation based on the computed one or more properties and one or more predefined rules, wherein the nodes corresponding to the AMI devices are updated based on the computed one or more properties and the one or more links are modified based on the one or more predefined rules; select one or more nodes in the modified graphical representation and process the selected one or more nodes in an order based on AMI device hierarchy, priority and criticality; modify the graphical representation based on the processing of the selected nodes; and identify AMI devices with communication failures from at least one of the generated and modified graphical representation of the AMI devices.